{"id":"https://openalex.org/W4414888830","doi":"https://doi.org/10.1109/icmla66185.2025.00050","title":"Localized LoRA: A Structured Low-Rank Approximation for Efficient Fine-Tuning","display_name":"Localized LoRA: A Structured Low-Rank Approximation for Efficient Fine-Tuning","publication_year":2025,"publication_date":"2025-12-03","ids":{"openalex":"https://openalex.org/W4414888830","doi":"https://doi.org/10.1109/icmla66185.2025.00050"},"language":"en","primary_location":{"id":"doi:10.1109/icmla66185.2025.00050","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmla66185.2025.00050","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Machine Learning and Applications (ICMLA)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2506.00236","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067095879","display_name":"Babak Barazandeh","orcid":"https://orcid.org/0000-0003-3568-8450"},"institutions":[{"id":"https://openalex.org/I4210159548","display_name":"Risk Engineering (Bulgaria)","ror":"https://ror.org/051e4zg07","country_code":"BG","type":"company","lineage":["https://openalex.org/I4210159548"]}],"countries":["BG"],"is_corresponding":true,"raw_author_name":"Babak Barazandeh","raw_affiliation_strings":["AI Risk and Vulnerability Alliance"],"affiliations":[{"raw_affiliation_string":"AI Risk and Vulnerability Alliance","institution_ids":["https://openalex.org/I4210159548"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042095646","display_name":"Subhabrata Majumdar","orcid":"https://orcid.org/0000-0003-3529-7820"},"institutions":[{"id":"https://openalex.org/I4210152072","display_name":"St. John International University","ror":"https://ror.org/0090r4223","country_code":"IT","type":"education","lineage":["https://openalex.org/I4210152072"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Subhabrata Majumdar","raw_affiliation_strings":["Vijil"],"affiliations":[{"raw_affiliation_string":"Vijil","institution_ids":["https://openalex.org/I4210152072"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119875960","display_name":"Om Rajyaguru","orcid":null},"institutions":[{"id":"https://openalex.org/I4210159548","display_name":"Risk Engineering (Bulgaria)","ror":"https://ror.org/051e4zg07","country_code":"BG","type":"company","lineage":["https://openalex.org/I4210159548"]}],"countries":["BG"],"is_corresponding":false,"raw_author_name":"Om Rajyaguru","raw_affiliation_strings":["AI Risk and Vulnerability Alliance"],"affiliations":[{"raw_affiliation_string":"AI Risk and Vulnerability Alliance","institution_ids":["https://openalex.org/I4210159548"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017220650","display_name":"George Michailidis","orcid":"https://orcid.org/0000-0002-3676-1739"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"George Michailidis","raw_affiliation_strings":["University of California,Los Angeles"],"affiliations":[{"raw_affiliation_string":"University of California,Los Angeles","institution_ids":["https://openalex.org/I161318765"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5067095879"],"corresponding_institution_ids":["https://openalex.org/I4210159548"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26525124,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"324","last_page":"329"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9837999939918518,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9837999939918518,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11034","display_name":"Digital Filter Design and Implementation","score":0.9825999736785889,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9794999957084656,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/parameter-space","display_name":"Parameter space","score":0.49059998989105225},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4778999984264374},{"id":"https://openalex.org/keywords/approximation-algorithm","display_name":"Approximation algorithm","score":0.3610000014305115},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.3562999963760376},{"id":"https://openalex.org/keywords/low-rank-approximation","display_name":"Low-rank approximation","score":0.35269999504089355},{"id":"https://openalex.org/keywords/approximation-theory","display_name":"Approximation theory","score":0.3172000050544739},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.31450000405311584}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.579200029373169},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.524399995803833},{"id":"https://openalex.org/C73586568","wikidata":"https://www.wikidata.org/wiki/Q2600211","display_name":"Parameter space","level":2,"score":0.49059998989105225},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4778999984264374},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.38690000772476196},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3677999973297119},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.3610000014305115},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.3562999963760376},{"id":"https://openalex.org/C90199385","wikidata":"https://www.wikidata.org/wiki/Q6692777","display_name":"Low-rank approximation","level":3,"score":0.35269999504089355},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.34940001368522644},{"id":"https://openalex.org/C145242015","wikidata":"https://www.wikidata.org/wiki/Q774123","display_name":"Approximation theory","level":2,"score":0.3172000050544739},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.31450000405311584},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.3107999861240387},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.30300000309944153},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.29010000824928284},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C3018263672","wikidata":"https://www.wikidata.org/wiki/Q1296251","display_name":"Efficient algorithm","level":2,"score":0.27059999108314514},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.26820001006126404},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26570001244544983},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.25519999861717224}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icmla66185.2025.00050","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmla66185.2025.00050","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Machine Learning and Applications (ICMLA)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2506.00236","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.00236","pdf_url":"https://arxiv.org/pdf/2506.00236","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2506.00236","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2506.00236","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2506.00236","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.00236","pdf_url":"https://arxiv.org/pdf/2506.00236","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Parameter-efficient":[0],"fine-tuning":[1,15,137],"(PEFT)":[2],"methods,":[3,134],"such":[4],"as":[5,56],"LoRA,":[6,48],"offer":[7],"compact":[8],"and":[9,95,100,118,129],"effective":[10],"alternatives":[11],"to":[12,20,63,132],"full":[13],"model":[14],"by":[16],"introducing":[17],"low-rank":[18,30,60,98],"updates":[19,55,75],"pretrained":[21],"weights.":[22],"However,":[23],"most":[24],"existing":[25,133],"approaches":[26],"rely":[27],"on":[28,115],"global":[29],"structures,":[31],"which":[32],"can":[33],"overlook":[34],"spatial":[35],"patterns":[36],"spread":[37],"across":[38],"the":[39,67,77,81],"parameter":[40,78,112],"space.":[41],"In":[42],"this":[43],"work,":[44],"we":[45],"propose":[46],"Localized":[47,123],"a":[49,57,89,126],"generalized":[50],"framework":[51],"that":[52,102,122],"models":[53],"weight":[54,68],"composition":[58],"of":[59,66,84],"matrices":[61],"applied":[62],"structured":[64],"blocks":[65],"matrix.":[69],"This":[70],"formulation":[71],"enables":[72],"dense,":[73],"localized":[74,97],"throughout":[76],"space\u2014without":[79],"increasing":[80],"total":[82],"number":[83],"trainable":[85],"parameters.":[86],"We":[87],"provide":[88],"formal":[90],"comparison":[91],"between":[92],"global,":[93],"diagonal-local,":[94],"fully":[96],"approximations,":[99],"show":[101],"our":[103],"method":[104],"consistently":[105],"achieves":[106],"lower":[107],"approximation":[108],"error":[109],"under":[110],"matched":[111],"budgets.":[113],"Experiments":[114],"both":[116],"synthetic":[117],"practical":[119],"settings":[120],"demonstrate":[121],"LoRA":[124],"offers":[125],"more":[127],"expressive":[128],"adaptable":[130],"alternative":[131],"enabling":[135],"efficient":[136],"with":[138],"improved":[139],"performance.":[140]},"counts_by_year":[],"updated_date":"2026-04-09T06:08:40.794217","created_date":"2025-10-10T00:00:00"}
